Data Analyst — Jira Data Normalization / Migration Analysis

Data Analyst - Jira Data Normalization / Migration Analysis (W2 or C2C) Project description We are seeking a Data Analyst to support the analysis, profiling, normalization, deduplication, and validation of Jira data from multiple source repositories. This role will work closely with ETL developers, Jira administrators, QA testers, and business stakeholders to define source-to-target mappings, identify data quality issues, validate transformation logic, and ensure the migrated Jira data is accurate, complete, and usable in the new Jira configuration. Responsibilities Analyze Jira data from multiple source repositories to understand structure, quality, completeness, and inconsistencies. Profile source data across Jira projects, issues, users, workflows, statuses, custom fields, labels, components, comments, attachments, and history. Document source-to-target mappings for migration into the new Jira configuration. Identify duplicate records across repositories and help define deduplication rules. Support business rule definition for data normalization, field standardization, naming conventions, project mapping, and user mapping. Work with stakeholders to clarify data ownership, field usage, transformation rules, and reporting requirements. Validate archived Jira data in Snowflake for reporting continuity. Create data quality reports, exception reports, reconciliation reports, and migration readiness dashboards. Support user acceptance testing by preparing validation scenarios and sample datasets. Partner with QA testers to define test cases and expected results. Review migration outputs and compare source versus target data for completeness and accuracy. Assist with cutover planning, dry-run analysis, and post-migration validation. Source data profiling reports. Source-to-target mapping documents. Data normalization rules. Deduplication rule documentation. Data quality issue logs. Migration reconciliation reports. Snowflake archival validation reports. UAT support documentation. Business validation sign-off support. Skills Must have Strong data analysis experience, preferably in migration, consolidation, or data quality initiatives. Strong SQL skills for querying, profiling, reconciliation, and validation. Experience analyzing structured and semi-structured data. Ability to create clear source-to-target mapping documents. Experience with data quality dimensions such as completeness, uniqueness, consistency, validity, and referential integrity. Strong understanding of deduplication, matching logic, exception handling, and reconciliation. Ability to translate business requirements into data rules and validation criteria. Strong documentation and stakeholder communication skills. #J-18808-Ljbffr Goldenpick Technologies